The device-to-device (D2D) communication is viewed as an attractive technique to increase the spectrum efficiency and the data transmission rate in the wireless network. In this paper, we investigate the joint resource allocation and power control problem for cooperative D2D users (DUs) which multiplex cellular users (CUs) in downlink cooperative D2D heterogeneous networks. The studied resource allocation problem contains the spectrum resource block allocation and the selection of an idle user which works as a relay to assist the D2D links communication, while the power control aims to reduce the interference between users and improve the communication quality of service (QoS). To efficiently maximize the total throughput of all the DU links and the CU links on the premise of guaranteeing the communication QoS for CUs, we propose a quantum coral reefs optimization algorithm (QCROA) to obtain the optimal joint resource allocation and power control scheme. The simulation results demonstrate that the proposed QCROA achieves an excellent performance for different network communication scenarios.

We design a co-time co-frequency full-duplex (CCFD) massive multiple-input multiple-output (MIMO) network to improve the utilization of time-frequency resources and physical layer security. Simultaneous information transmissions of the base station and the users are regarded as same-frequency interference against interception by eavesdroppers. To promote energy conservation and improve utilization of system resources, we propose a joint antenna selection and power allocation (JASPA) strategy for CCFD massive MIMO networks. Considering the trade-off between secrecy performance and system communications quality, we formulate optimization functions based on JASPA for two security concerns. We design a quantum-inspired backtracking search algorithm (QBSA) to obtain the optimal JASPA scheme. Simulation results show that the performance of the proposed QBSA is superior to previous intelligent algorithms in CCFD massive MIMO systems. The effectiveness of the proposed JASPA scheme is demonstrated under various communications scenarios, and can be considered a cornerstone for future research in wireless communications domain.

This paper presents a co-time co-frequency full-duplex (CCFD) massive multiple-input multiple-output (MIMO) system to meet high spectrum efficiency requirements for beyond the fifth-generation (5G) and the forthcoming the sixth-generation (6G) networks. To achieve equilibrium of energy consumption, system resource utilization, and overall transmission capacity, an energy-efficient resource management strategy concerning power allocation and antenna selection is designed. A continuous quantum-inspired termite colony optimization (CQTCO) algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO system. The effectiveness of CQTCO compared with other algorithms is evaluated through simulations. The results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios, which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.

For intelligent reflecting surface (IRS)-aided networks, it is known that high network performance requires a large surface of IRS due to multiple path losses. Moreover, if a secure communication system wants to obtain a higher secrecy rate, more passive reflecting elements are needed, resulting in larger size of IRS. However, even though we increase more elements of IRS, we will face the problem of limited performance improvement. To solve this problem, we propose a secure communication architecture where an intelligent mixed reflecting/relaying surface (IMRRS) aids information transmission. We formulate the exact secrecy energy efficiency expression, and then aim to design an energy-efficient scheme to realize intelligent reflecting element (IRE) working mode selection and secure dynamic hybrid resource management. To address the formulated problem, we propose a fast IRE working mode selection method and a quantum-inspired bald eagle search (QBES) algorithm. Simulation results demonstrate the superiority of the proposed method, which can exploit the IMRRS benefits and improve security performance during information transmission.

Energy harvesting (EH) technology is considered to be a promising approach to provide enough energy for energy-constrained Internet of Things (IoT). In this paper, we propose an energy harvesting and information transmission mode for the spectrum sharing system with cooperative EH-abled IoT applications in beyond 5G networks. Different from most existing IoT spectrum-sharing research studies, in our system, both primary user (PU) and IoT devices (IDs) collect energy for their information transmission. In addition, for all IDs, they should realize two communication functions: working as relays to help the information transfer process of PU and completing their own information transmission. We analytically derive exact expressions for the throughput of the primary system and IoT system and then formulate two objective functions. It is easy to see that power splitting ratio, dynamic EH ratio, power sharing ratio, and relay selection should be optimized to get the best performance for different communication circumstances. Actually, it is a hybrid NP-hard problem to optimize these parameters and traditional algorithms cannot solve it well. Therefore, a novel algorithm-quantum whale optimization algorithm (QWOA) is proposed to obtain the best performance. Simulation results show the good performance of QWOA in different simulation scenarios.